Harenslak B. Data Pipelines with Apache Airflow 2021 torrent

Textbook in PDF format

Data Pipelines with Apache Airflow teaches you the ins-and-outs of the Directed Acyclic Graphs (DAGs) that power Airflow, and how to write your own DAGs to meet the needs of your projects. With complete coverage of both foundational and lesser-known features, when you’re done you’ll be set to start using Airflow for seamless data pipeline development and management.
Pipelines can be challenging to manage, especially when your data has to flow through a collection of application components, servers, and cloud services. Airflow lets you schedule, restart, and backfill pipelines, and its easy-to-use UI and workflows with Python scripting has users praising its incredible flexibility. Data Pipelines with Apache Airflow takes you through best practices for creating pipelines for multiple tasks, including data lakes, cloud deployments, and data science.
Data Pipelines with Apache Airflow teaches you the ins-and-outs of the Directed Acyclic Graphs (DAGs) that power Airflow, and how to write your own DAGs to meet the needs of your projects. With complete coverage of both foundational and lesser-known features, when you’re done you’ll be set to start using Airflow for seamless data pipeline development and management.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Getting Started
Meet Apache Airflow
Anatomy of an Airflow DAG
Scheduling in Airflow
Templating tasks using the Airflow context
Defining dependencies between tasks
Beyond the Basics
Triggering workflows
Communicating with external systems
Building custom components
Testing
Running tasks in containers
Airflow in Practice
Best practices
Operating Airflow in production
Securing Airflow
Project: Finding the fastest way to get around NYC
In the Clouds
Airflow in the clouds
Airflow on AWS
Airflow on Azure
Airflow in GCP
Appendixes
Running code samples
Package structures Airflow 1 and 2
Prometheus metric mapping